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.
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,
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.
1
,
A
p
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l
2021
,
p
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129
~
136
IS
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25
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R
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202
1
A
c
c
e
pt
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d
J
a
n
2
9
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202
1
In
t
hi
s
w
o
r
k
,
we
us
e
d
a
ne
w
a
p
pr
o
a
c
h
as
a
c
t
i
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qu
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m
a
n
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g
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nt
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A
Q
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to
a
v
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t
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c
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s
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C
P
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ne
t
w
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ks
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he
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h
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o
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s
w
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pt
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m
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z
a
t
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n
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P
S
O
)
a
l
g
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r
i
t
hm
as
an
o
pt
i
m
i
z
a
t
i
o
n
t
e
c
hni
que
to
i
m
pr
o
v
e
t
he
pe
r
f
o
r
m
a
nc
e
of
t
he
PI
c
o
nt
r
o
l
l
e
r
a
nd
t
he
r
e
f
o
r
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i
m
pr
o
v
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ng
t
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pe
r
f
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m
a
nc
e
of
T
C
P
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I
P
ne
t
w
o
r
ks
as
a
r
e
qu
i
r
e
d
g
o
a
l
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T
he
o
pt
i
m
i
z
a
t
i
o
n
c
o
nt
r
o
l
(
P
S
O
-
P
I
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is
c
ha
r
a
c
t
e
r
i
z
e
d
by
a
c
c
e
s
s
to
de
s
i
g
n
a
nd
c
ho
o
s
i
ng
t
h
e
o
pt
i
m
a
l
pa
r
a
m
e
t
e
r
s
of
(
K
_i
a
ndK
_
p)
to
r
e
a
c
h
o
pt
i
m
a
l
s
o
l
u
t
i
o
ns
in
a
s
ho
r
t
w
a
y
(
f
e
w
e
r
i
t
e
r
a
t
i
o
ns
)
.
T
he
i
m
p
l
e
m
e
n
t
a
t
i
o
n
of
t
he
PSO
a
l
g
o
r
i
t
hm
is
a
c
hi
e
v
i
ng
by
us
i
ng
t
he
m
a
t
h
e
m
a
t
i
c
a
l
s
y
s
t
e
m
m
o
de
l
a
nd
M
-
f
i
l
e
a
nd
S
I
M
U
L
I
N
K
in
M
a
t
h
l
a
b
pr
o
g
r
a
m
.
S
i
m
ul
a
t
i
o
n
r
e
s
ul
t
s
s
ho
w
g
oo
d
c
o
ng
e
s
t
i
o
n
m
a
na
g
e
m
e
n
t
pe
r
f
o
r
m
a
nc
e
w
i
t
h
PSO
-
PI
c
o
nt
r
o
l
l
e
r
be
t
t
e
r
t
ha
n
t
he
PI
c
o
nt
r
o
l
l
e
r
as
A
QM
in
T
C
P
ne
t
w
o
r
k
s
,
a
n
d
t
he
p
r
o
po
s
e
d
m
e
t
ho
d
w
a
s
v
e
r
y
f
a
s
t
a
nd
r
e
qu
i
r
e
d
f
e
w
i
t
e
r
a
t
i
o
ns
.
Ke
y
w
or
d
s
:
AQM
PI
c
o
n
t
r
o
l
l
e
r
PSO
T
CP
T
hi
s
is
an
ope
n
ac
c
e
s
s
ar
t
i
c
l
e
u
nde
r
t
he
CC
BY
-
SA
l
i
c
e
ns
e
.
Cor
r
e
s
pon
di
n
g
Au
t
h
or
:
S
a
l
a
m
W
a
l
e
y
S
hn
e
e
n
E
n
e
rgy
a
n
d
R
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n
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w
a
b
l
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E
n
e
r
gi
e
s
T
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c
hn
o
l
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g
y
Ce
n
t
e
r
T
h
e
U
n
i
v
e
r
s
i
ty
of
T
e
c
h
n
o
l
o
g
y
5
2
Al
-
S
na
a
s
t
r
e
e
t
,
B
a
g
h
d
a
d,
I
ra
q
E
m
a
i
l
:
50054
@
uo
t
e
c
hn
o
l
o
g
y
.
e
du.
i
q
1.
I
N
TR
O
D
U
C
TI
O
N
T
h
e
i
n
c
r
e
a
s
e
in
da
t
a
c
i
r
c
ul
a
t
i
ng
on
t
h
e
I
nt
e
rn
e
t
a
n
d
th
e
i
n
c
r
e
a
s
e
in
t
h
e
n
u
m
b
e
r
of
In
t
e
rn
e
t
us
e
r
s
ha
s
m
a
de
t
h
e
n
e
t
w
o
r
k
m
o
r
e
c
o
n
ge
s
t
e
d
[1
-
3]
.
A
m
o
n
g
t
h
e
p
r
o
b
l
e
m
s
t
ha
t
r
e
s
e
a
r
c
h
e
r
s
w
o
r
k
in
t
h
e
f
i
e
l
d
of
I
n
t
e
rn
e
t
us
e
,
s
uc
h
as
b
uffe
r
ov
e
r
f
l
ow
fo
r
i
nt
e
rm
e
di
a
t
e
v
e
c
t
o
r
s
,
l
o
s
s
of
pa
c
k
e
t
s
a
n
d
t
i
m
e
de
l
a
y
in
t
h
e
de
l
i
v
e
r
y
of
pa
c
ke
t
s
[4
-
6].
To
i
m
p
r
o
v
e
n
e
t
w
o
r
k
pe
r
f
o
r
m
a
n
c
e
,
t
h
e
us
e
of
t
ra
n
s
m
i
s
s
i
o
n
c
o
n
t
r
o
l
pr
o
t
o
c
o
l
a
n
d
a
c
t
i
v
e
que
ue
m
a
na
ge
m
e
n
t
(
T
CP
/
A
Q
M
).
AQM
w
a
s
t
h
e
m
a
i
n
po
l
i
c
y
us
e
d
fo
r
c
o
n
t
r
o
l
[7
-
9]
.
To
o
ve
r
c
o
m
e
t
h
e
s
e
pr
o
b
l
e
m
s
.
T
h
e
PSO
a
l
go
r
i
t
h
m
is
o
n
e
of
t
h
e
di
s
t
i
n
c
t
i
v
e
m
e
t
h
o
d
s
us
e
d
by
r
e
s
e
a
r
c
h
e
r
s
to
s
o
l
v
e
n
o
n
l
i
n
e
a
ri
t
y
a
n
d
n
o
n
-
di
f
fe
r
e
nt
i
a
t
i
o
n
p
r
o
b
l
e
m
s
a
n
d
to
i
m
p
r
o
v
e
pe
r
f
o
r
m
a
n
c
e
to
r
e
a
c
h
a
d
a
pt
a
t
i
o
n
[10
-
12].
T
h
e
f
i
r
s
t
to
s
ugge
s
t
PSO
a
l
go
ri
t
hm
is
K
e
nn
e
dy
a
n
d
E
b
e
r
ha
rt
[13]
.
It
is
a
m
e
t
h
o
d
fo
r
de
ve
l
o
pi
n
g
f
l
o
c
k
r
e
s
e
a
r
c
h,
s
uc
h
as
g
a
t
h
e
r
i
ng
b
i
r
ds
a
n
d
ke
e
pi
n
g
f
i
s
h
[14
,
15]
.
T
h
e
o
pt
i
m
i
z
a
t
i
o
n
PSO
is
c
ha
ra
c
t
e
ri
z
e
d
by
a
c
o
m
b
i
n
a
t
i
o
n
of
a
l
go
r
i
t
hm
s
t
ha
t
i
m
p
r
o
v
e
pe
r
f
o
r
m
a
n
c
e
b
e
t
t
e
r
t
h
a
n
o
t
h
e
r
s
,
w
hi
c
h
a
r
e
go
o
d
e
f
f
i
c
i
e
n
c
y
,
r
e
l
a
t
i
v
e
s
i
m
pl
i
c
i
t
y
,
a
n
d
s
t
a
b
l
e
c
o
n
v
e
r
ge
n
c
e
pr
o
pe
rt
y
[16
-
18].
D
e
s
i
g
n
PSO
-
P
ID
as
a
c
o
n
t
r
o
l
u
n
i
t
for
pe
r
f
o
r
m
a
n
c
e
e
s
t
i
m
a
t
i
o
n
us
i
n
g
t
h
e
IT
A
E
s
t
a
n
d
a
r
d
as
o
n
e
of
t
h
e
s
i
m
pl
e
s
t
a
n
d
m
o
s
t
t
i
m
e
-
s
a
v
i
n
g
a
pp
l
i
c
a
t
i
o
n
s
for
pe
r
f
o
r
m
a
n
c
e
m
e
a
s
u
r
e
m
e
nt
[1
9
-
21]
.
T
h
e
IT
S
E
pe
r
f
o
rm
a
n
c
e
s
t
a
n
da
rd
w
e
i
gh
s
e
rr
o
r
s
o
ve
r
t
i
m
e
,
pe
na
l
i
z
e
s
s
m
a
l
l
e
rr
o
r
s
at
a
l
a
t
e
r
t
i
m
e
a
n
d
di
s
t
i
n
gu
i
s
h
e
s
l
a
r
ge
i
n
i
t
i
a
l
e
rr
o
r
in
r
e
s
po
n
s
e
.
To
de
s
i
gn
c
o
n
t
r
o
l
l
e
r
s
unde
r
t
he
go
a
l
of
t
r
y
i
n
g
to
r
e
duc
e
s
y
s
t
e
m
e
r
r
o
r
r
e
s
ul
t
i
n
g
f
r
o
m
s
e
ve
r
a
l
p
r
e
di
c
t
a
b
l
e
i
n
p
ut
s
[2
2
-
24]
.
S
y
s
t
e
m
e
r
r
o
r
is
t
h
e
di
f
fe
r
e
n
c
e
b
e
t
w
e
e
n
t
h
e
de
s
i
r
e
d
r
e
s
po
n
s
e
a
n
d
t
h
e
a
c
t
ua
l
s
y
s
t
e
m
r
e
s
po
n
s
e
.
A
m
o
ng
t
h
e
a
pp
r
o
v
e
d
s
t
a
n
da
r
ds
t
ha
t
de
t
e
r
m
i
n
e
pe
r
f
o
r
m
a
n
c
e
a
r
e
t
h
o
s
e
t
ha
t
a
r
e
m
a
i
nl
y
b
a
s
e
d
on
t
h
e
e
rr
o
r
s
c
a
l
e
in
t
h
e
s
y
s
t
e
m
[25
-
27].
In
ge
n
e
ra
l
,
t
ra
di
t
i
o
n
a
l
c
o
n
t
r
o
l
l
e
r
s
s
uc
h
as
P
ID
c
a
n
be
de
s
i
gn
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
,
V
o
l
.
22
,
N
o
.
1
,
A
p
r
i
l
20
21
:
129
-
1
36
130
in
s
uc
h
a
w
a
y
as
to
us
e
o
n
e
of
t
h
e
f
o
r
m
a
t
s
of
a
pe
r
f
o
r
m
a
n
c
e
s
t
a
n
da
rd
t
ha
t
i
n
c
l
ude
s
(IA
E
)
,
(IS
E
),
(I
T
S
E
)
or
(IT
A
E
)
in
c
o
n
t
r
o
l
[28
-
30].
Q
a
r
a
d
a
w
i
,
S.
e
t
al
.
t
h
e
y
us
e
d
a
PI
c
o
n
t
r
o
l
l
e
r
w
i
t
h
PSO
as
an
AQM
to
a
v
o
i
d
t
h
e
c
o
n
ge
s
t
i
o
n
in
c
o
m
put
e
r
n
e
t
w
o
r
ks
,
t
h
e
s
i
m
ul
a
t
i
o
n
r
e
s
ul
t
s
a
ppe
a
r
e
d
a
go
o
d
r
e
s
po
n
s
e
t
i
m
e
w
i
t
h
a
co
n
s
t
a
nt
v
a
l
ue
of
o
ut
put
[31].
N
a
y
l
,
T.
M
.
,
e
t
al
.
t
h
e
y
pr
o
po
s
e
d
a
de
s
i
gn
AQM
fo
r
T
CP
n
e
t
w
o
r
k
c
o
n
s
i
s
t
e
d
of
(L
Q
)
-
s
e
r
v
o
c
o
n
t
r
o
l
l
e
r
w
i
t
h
PSO
m
e
t
h
o
d
to
r
e
duc
e
t
h
e
de
l
a
y
t
i
m
e
,
f
o
s
t
e
r
i
n
g
s
e
t
t
l
i
n
g
t
i
m
e
a
nd
p
r
o
v
i
de
a
s
t
a
b
l
e
que
ue
l
e
n
gt
h
[3
2].
L
i
,
Z.
H.
E
.
,
e
t
a
l
,
th
ey
s
ugge
s
t
e
d
a
n
e
w
AQM
a
pp
r
o
a
c
h
for
a
t
y
p
e
of
T
CP
n
e
t
w
o
r
k
by
us
i
n
g
an
i
nt
e
g
r
a
l
b
a
c
k
-
s
t
e
ppi
n
g
t
e
c
hni
que
(IB
)
a
n
d
m
i
n
i
m
a
x
p
r
o
c
e
dur
e
,
t
h
e
r
e
s
ul
t
s
s
h
o
w
e
d
a
s
h
o
r
t
c
o
n
v
e
r
ge
nt
du
r
a
t
i
o
n
a
n
d
de
a
l
w
i
t
h
t
h
e
di
s
o
r
de
r
s
p
r
o
duc
e
d
by
UDP
s
t
r
e
a
m
s
[33]
.
K
a
d
h
i
m
,
H.
M
.
,
e
t
a
l
,
t
h
e
y
de
s
i
gn
e
d
t
y
pe
-
1
a
n
d
t
y
pe
-
2
f
uz
z
y
l
o
gi
c
w
i
t
h
P
ID
c
o
n
t
r
o
l
l
e
r
to
r
e
duc
e
t
h
e
c
o
n
ge
s
t
i
o
n
in
t
he
T
CP
n
e
t
w
o
r
ks
w
h
e
n
t
h
e
y
us
e
d
o
pt
i
m
i
z
a
t
i
o
n
a
l
go
ri
t
hm
s
(P
S
O
,
SSO
a
nd
A
CO
)
to
c
h
oo
s
e
t
h
e
pa
ra
m
e
t
e
r
s
of
t
w
o
c
o
n
t
r
o
l
l
e
r
s
,
t
y
pe
-
2
f
uz
z
y
l
o
gi
c
w
i
t
h
SSO
ha
s
g
i
v
e
n
go
o
d
r
e
s
ul
t
s
[3
4].
T
h
i
s
w
o
r
k
p
r
o
po
s
e
s
us
i
n
g
a
p
r
o
po
r
t
i
o
n
a
l
i
nt
e
g
r
i
t
y
c
o
n
t
r
o
l
l
e
r
(P
I)
w
i
t
h
a
l
go
r
i
t
h
m
(P
S
O
)
as
an
a
c
t
i
v
e
que
ue
m
a
n
a
ge
r
for
I
nt
e
rn
e
t
r
o
ut
e
r
s
.
T
h
e
go
a
l
s
of
t
h
e
w
o
r
k
go
t
o
w
a
r
d
f
ul
f
i
l
l
i
n
g
a
s
t
a
b
l
e
que
ue
l
e
n
gt
h,
i
m
p
r
o
v
e
l
a
t
e
n
c
y
to
pr
e
v
e
n
t
T
CP
f
a
i
l
u
r
e
or
s
l
o
w
i
n
g
do
w
n
.
T
h
e
s
t
ruc
t
u
re
of
t
h
e
p
a
pe
r
is
o
r
ga
ni
z
e
d
as
f
o
l
l
o
w
s
,
S
e
c
t
i
o
n
2,
i
n
c
l
ude
t
h
e
S
i
m
u
l
i
n
k
m
o
de
l
for
T
CP
/
A
Q
M
s
y
s
t
e
m
.
T
h
e
s
i
m
ul
a
t
i
o
n
r
e
s
ul
t
s
w
r
o
t
e
do
w
n
in
S
e
c
t
i
o
n
3.
T
h
e
c
o
n
c
l
us
i
o
n
of
t
h
i
s
w
o
r
k
w
r
o
t
e
in
S
e
c
t
i
o
n
4.
2.
S
I
M
U
LI
N
K
M
O
D
EL
F
O
R
TC
P
/
A
Q
M
S
Y
S
T
EM
T
CP
/
A
Q
M
n
e
t
w
o
r
k,
in
F
i
gu
r
e
1
m
o
de
l
S
y
s
t
e
m
of
T
CP
/
A
Q
M
n
e
t
w
o
r
ks
t
ha
t
i
n
c
l
u
de
s
r
o
ut
e
r
s
,
s
o
ur
c
e
s
,
a
n
d
s
t
a
n
d
a
r
di
z
e
d
c
o
n
t
r
o
l
n
e
t
w
o
r
ks
,
F
i
gu
r
e
2
s
c
h
e
m
a
t
i
c
m
o
de
l
S
y
s
t
e
m
of
a
c
o
n
t
r
o
l
l
e
r
w
i
t
h
AQM
n
e
t
w
o
r
k
a
n
d
t
h
e
s
y
s
t
e
m
b
l
oc
k
di
a
g
ra
m
of
T
CP
/
A
Q
M
n
e
t
w
o
r
k
in
F
i
g
u
r
e
3.
F
i
gu
r
e
1.
S
y
s
t
e
m
of
T
CP
/
AQM
n
e
t
w
o
r
ks
F
i
gu
r
e
2.
S
c
h
e
m
a
t
i
c
m
o
de
l
of
a
c
o
n
t
r
o
l
l
e
r
w
i
t
h
a
T
CP
n
e
t
w
o
r
k
F
i
gu
r
e
3.
S
y
s
t
e
m
b
l
oc
k
di
a
g
ra
m
of
T
CP
/
A
Q
M
n
e
t
w
o
r
k
q
p
e
-
q
re
f
+
A
QM
c
on
tr
ol
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
D
e
s
i
gn
and
i
m
p
l
e
m
e
nt
a
t
i
on
o
f
a
s
t
a
bi
l
i
t
y
c
on
t
r
ol
s
y
s
t
e
m
f
or
T
CP
/
A
Q
M
ne
t
w
or
k
(
Sal
am
W
al
e
y
Shn
e
e
n
)
131
In
t
hi
s
s
e
c
t
i
o
n,
it
ha
d
t
w
o
pa
rt
s
f
i
r
s
t
p
a
r
t
is
t
h
e
S
i
m
ul
i
n
k
m
o
de
l
of
t
h
e
PI
c
o
nt
r
o
l
l
e
r
for
T
CP
/
A
Q
M
t
h
a
t
s
h
o
w
in
F
i
gu
r
e
4.
T
h
e
S
i
m
u
l
i
nk
m
o
de
l
of
PI
fo
r
T
CP
/
A
Q
M
,
it
ha
d
i
n
pu
t
,
PI
c
o
n
t
r
o
l
l
e
r
,
T
.
F
of
T
CP
/
A
Q
M
a
n
d
o
ut
put
.
T
h
e
s
e
c
o
n
d
pa
rt
is
t
h
e
S
i
m
ul
i
n
k
m
o
de
l
of
P
S
O
-
PI
for
T
CP
/
A
Q
M
s
h
o
w
n
in
F
i
gu
r
e
5.
T
h
e
S
i
m
ul
i
n
k
m
o
de
l
of
PSO
-
PI
fo
r
T
CP
/
A
Q
M
,
it
ha
d
i
n
pu
t
,
PI
c
o
n
t
r
o
l
l
e
r
w
i
t
h
IT
A
E
,
T
.
F
of
T
CP
/
A
Q
M
a
n
d
o
ut
put
.
T
a
b
l
e
1
s
h
o
w
i
n
g
t
h
e
v
a
l
ue
s
of
T
CP
/
A
Q
M
n
e
t
w
o
r
k
t
o
po
l
o
g
y
t
h
a
t
we
h
a
v
e
a
do
pt
e
d
on
our
w
o
r
k.
T
h
e
m
a
t
h
e
m
a
t
i
c
a
l
m
o
de
l
of
t
h
e
TC
P
n
e
t
w
o
r
k
as
s
h
o
w
n
in
(1
-
6)
[
35
-
38]:
"
w
̇
t
=
1
q
t
C
+
T
p
−
w
t
2
w
(
t
R
t
)
q
(
t
−
R
t
)
C
+
T
p
p
t
−
R
t
"
(1)
"
q
̇
t
=
{
−
C
N
t
q
t
C
+
T
p
w
t
if
q
t
>
0
ma
x
{
0
,
−
C
N
t
q
t
C
+
T
p
w
t
}
if
q
t
=
0
(2)
122
.
8
s
3
+
3
2
99
s
2
+
2455s
+
3
.
252
e
04
s
4
+
1
.
136
s
3
+
20
.
14
s
2
+
11
.
26s
+
99
.
8
(3)
F
s
=
q
s
p
s
=
C
2
2N
e
−
sR
s
+
2N
R
2
C
s
+
1
R
(4)
sa
t
(
p
(
t
−
R
t
)
)
=
{
1
,
p
(
t
−
R
t
)
≥
1
p
(
t
−
R
t
)
,
0
≤
p
(
t
−
R
t
)
<
1
0
,
p
(
t
−
R
t
)
<
0
(5)
W
h
e
r
e
:
̇
a
n
d
̇
is
t
h
e
t
i
m
e
-
de
r
i
v
a
t
i
v
e
of
w
a
nd
q
r
e
s
pe
c
t
i
v
e
l
y
.
w
:
R
a
t
e
of
T
CP
w
i
n
do
w
s
i
z
e
,
R
:
m
e
a
s
u
r
e
d
in
s
e
c
o
n
ds
,
R
=
q
C
T
p
q:
ra
t
e
of
que
ue
l
e
ngt
h
C
:
C
a
pa
c
i
t
y
of
t
h
e
l
i
n
k
N
:
L
o
a
d
f
a
c
t
o
r
T
p
:
P
r
o
m
ul
g
a
t
i
o
n
de
l
a
y
p
:
P
a
c
ke
t
s
i
g
n
p
r
o
b
a
b
i
l
i
t
y
s
t
=
K
P
e
t
K
I
∫
e
t
dt
t
0
(6)
W
h
e
r
e
:
e
t
:
T
h
e
e
rr
o
r
s
i
g
na
l
b
e
t
w
e
e
n
(t
h
e
i
n
pu
t
r
e
f
e
r
e
n
c
e
a
nd
t
h
e
p
r
o
c
e
s
s
o
ut
put
)
ec
t
:
T
h
e
c
h
a
n
ge
of
e
rr
o
r
s
i
g
na
l
:
P
r
o
po
r
t
i
o
n
a
l
c
o
n
s
t
a
n
t
g
a
i
n
:
I
nt
e
g
r
a
l
c
o
n
s
t
a
n
t
ga
i
n
F
i
gu
r
e
4.
S
i
m
u
l
i
n
k
m
o
de
l
of
PI
fo
r
T
CP
/
A
Q
M
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
,
V
o
l
.
22
,
N
o
.
1
,
A
p
r
i
l
20
21
:
129
-
1
36
132
F
i
gu
r
e
5.
S
i
m
u
l
i
n
k
m
o
de
l
of
PSO
-
PI
fo
r
T
CP
/
A
Q
M
T
a
b
l
e
1.
T
h
e
T
CP
n
e
t
w
o
r
k
p
a
r
a
m
e
t
e
r
s
y
s
t
e
m
N
C
P
a
c
k
e
t
s
i
z
e
Tp
R
q
d
e
s
q
m
a
x
60
15
M
b
p
s
500
b
y
t
e
0
.
2
s
e
c
o
n
d
s
0
.
2
5
3
s
e
c
o
n
d
s
300
p
a
c
k
e
t
s
700
p
a
c
k
e
t
s
(T
CP
s
e
s
s
i
o
n
n
u
m
b
e
r)
(3
7
5
0
p
a
c
k
e
t
/
s
e
c
o
n
d
s
l
i
n
k
c
a
p
a
c
i
t
y
)
-
(t
h
e
p
r
o
p
a
g
a
t
i
o
n
d
e
l
a
y
)
(t
h
e
r
o
u
n
d
-
t
r
i
p
t
i
m
e
)
(t
h
e
d
e
s
i
r
e
d
q
u
e
u
e
s
i
z
e
)
(m
a
x
i
m
u
m
q
u
e
u
e
l
e
n
g
t
h
in
r
o
u
t
e
r
1)
T
h
e
t
r
a
d
i
t
i
o
na
l
PI
c
o
n
t
r
o
l
l
e
r
s
a
re
us
e
d
in
m
a
n
y
a
ppl
i
c
a
t
i
o
ns
fo
r
po
s
i
t
i
o
n
a
nd
s
pe
e
d
c
o
n
t
r
o
l
,
t
h
e
s
e
c
o
n
t
r
o
l
l
e
r
m
e
t
h
o
ds
n
e
e
d
for
re
-
t
u
n
i
ng
its
pa
ra
m
e
t
e
r
s
b
e
c
a
us
e
it
s
o
m
e
t
i
m
e
s
d
o
e
s
n
o
t
gi
v
e
b
e
t
t
e
r
t
uni
n
g
a
nd
i
n
c
l
i
n
e
s
to
pr
o
duc
e
a
l
a
r
ge
o
v
e
r
s
h
o
o
t
.
To
boo
s
t
t
h
e
a
b
i
l
i
t
i
e
s
of
PI
pa
ra
m
e
t
e
r
t
u
ni
n
g,
di
f
f
e
r
e
n
t
i
n
t
e
l
l
i
ge
n
t
t
e
c
hn
i
q
ue
s
ha
v
e
b
e
e
n
p
r
o
po
s
e
d
to
i
m
p
r
o
v
e
t
h
e
PI
t
u
n
i
n
g
s
uc
h
as
ge
n
e
t
i
c
a
l
go
ri
t
hm
s
(G
A
)
[39
-
42
],
b
i
o
g
e
o
gr
a
p
h
y
b
a
s
e
d
o
pt
i
m
i
z
a
t
i
o
n
(B
B
O
)
[43
-
45]
,
a
nt
c
o
l
o
n
y
o
pt
i
m
i
z
a
t
i
o
n
(A
CO
)
[46]
,
b
e
e
c
o
l
o
n
y
o
pt
i
m
i
z
a
t
i
o
n
(B
CO
)
[47]
,
a
n
d
PSO.
T
h
e
t
e
c
hni
que
PSO
w
a
s
pr
o
po
s
e
d
in
t
hi
s
w
o
r
k
to
t
un
e
t
h
e
PI
c
o
n
t
r
o
l
l
e
r
pa
r
a
m
e
t
e
r
s
to
r
e
a
c
h
c
l
o
s
e
l
y
an
o
pt
i
m
a
l
pe
r
f
o
r
m
a
n
c
e
of
PI
c
ont
r
o
l
l
e
r
to
r
e
duc
e
t
h
e
e
f
fe
c
t
of
c
o
n
ge
s
t
i
o
n
in
T
CP
n
e
t
w
o
r
ks
,
for
m
o
r
e
de
t
a
i
l
s
a
b
o
ut
PSO
t
e
c
hni
que
you
c
a
n
r
e
v
i
e
w
R
e
f
s
,
[48
-
5
0
]
3.
S
I
M
U
LA
TI
O
N
R
ES
U
LTS
In
t
hi
s
s
e
c
t
i
o
n,
t
h
e
s
i
m
u
l
a
t
i
o
n
re
s
u
l
t
s
of
t
hi
s
w
o
r
k
a
r
e
p
r
e
s
e
nt
e
d
,
it
ha
d
t
w
o
pa
rt
s
,
t
he
f
i
r
s
t
p
a
rt
p
re
s
e
nt
s
t
h
e
S
i
m
u
l
i
nk
re
s
u
l
t
s
of
PI
c
o
nt
ro
l
l
e
r
for
T
CP
/
A
Q
M
t
ha
t
s
h
o
w
t
hro
u
g
h
t
he
F
i
gu
re
s
6
-
9
.
T
h
e
s
e
c
o
nd
p
a
rt
p
r
e
s
e
nt
s
t
h
e
S
i
m
u
l
i
nk
re
s
u
l
t
s
of
PSO
-
PI
c
o
nt
r
o
l
l
e
r
fo
r
T
CP
/
A
Q
M
t
ha
t
s
h
o
w
in
F
i
gu
re
s
10
,
11
.
T
h
e
s
u
m
m
a
r
y
of
a
l
l
S
i
m
u
l
i
nk
re
s
u
l
t
s
w
a
s
pu
t
in
T
a
b
l
e
2
w
i
t
h
t
he
i
m
po
rt
a
nt
v
a
l
ue
s
t
ha
t
we
go
t
t
h
r
o
ug
h
S
i
m
ul
i
nk
c
i
rc
u
i
t
s
.
F
i
gu
r
e
6.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
of
t
h
e
PI
c
o
n
t
r
o
l
l
e
r
for
c
a
l
c
ul
a
t
i
o
n
of
r
i
s
i
ng
t
i
m
e
(t
r
.)
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
D
e
s
i
gn
and
i
m
p
l
e
m
e
nt
a
t
i
on
o
f
a
s
t
a
bi
l
i
t
y
c
on
t
r
ol
s
y
s
t
e
m
f
or
T
CP
/
A
Q
M
ne
t
w
or
k
(
Sal
am
W
al
e
y
Shn
e
e
n
)
133
F
i
gu
r
e
7.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
of
t
h
e
PI
c
o
n
t
r
o
l
l
e
r
at
t
h
e
c
a
l
c
ul
a
t
i
o
n
of
s
t
e
a
dy
s
t
a
t
e
e
rr
o
r
(t
ss
.)
F
i
gu
r
e
8.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
PI
c
o
nt
r
o
l
l
e
r
for
c
a
l
c
ul
a
t
i
o
n
of
ove
r
s
h
o
o
t
(%)
F
i
g
u
r
e
9.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
PI
c
o
nt
r
o
l
l
e
r
for
c
a
l
c
ul
a
t
i
o
n
of
unde
r
s
h
o
o
t
(%)
F
i
gu
r
e
10
.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
of
PSO
-
PI
(IT
A
E
)
for
c
a
l
c
ul
a
t
i
o
n
of
r
i
s
i
ng
t
i
m
e
(t
r
.)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
,
V
o
l
.
22
,
N
o
.
1
,
A
p
r
i
l
20
21
:
129
-
1
36
134
F
i
gu
r
e
11
.
S
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
of
PSO
-
PI
(IT
A
E
)
for
c
a
l
c
ul
a
t
i
o
n
of
s
t
e
a
d
y
s
t
a
t
e
e
rr
o
r
(t
ss
.)
T
a
b
l
e
2
.
T
h
e
de
t
a
i
l
s
of
t
h
e
s
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
s
wi
th
t
h
e
f
i
gu
r
e
s
t
ha
t
s
h
o
w
t
h
e
s
e
r
e
s
ul
t
s
T
y
p
e
of
c
o
n
t
r
o
l
l
e
r
X
(t
i
m
e
)/
s
e
c
Y
(Q
u
e
u
e
s
i
z
e
)
(p
a
c
k
e
t
s
)
t
ss
t
r
O
v
e
r
s
h
o
o
t
U
n
d
e
r
s
h
o
o
t
F
i
g
u
r
e
Pi
0
.
0
2
8
9
8
210
0
.
0
2
8
9
8
6
Pi
0
.
6
2
9
7
2
9
9
.
6
0
.
6
2
9
7
7
Pi
0
.
0
9
1
5
8
4
1
0
.
9
(0
.
0
9
1
5
8
,
4
1
0
.
9
)
8
Pi
0
.
2
2
8
2
6
5
.
7
(0
.
2
2
8
,
2
6
5
.
7
)
9
P
s
o
-
pi
0
.
0
0
1
9
7
2
1
0
.
3
0
.
0
0
1
9
7
10
P
s
o
-
pi
0
.
1
4
3
6
300
0
.
1
4
3
6
11
S
t
e
p
r
e
s
po
n
s
e
of
t
h
e
PSO
-
PI
c
o
n
t
r
o
l
l
i
n
g
s
y
s
t
e
m
is
c
o
m
pl
e
t
e
l
y
di
ff
e
r
e
n
t
f
r
o
m
t
ha
t
of
t
h
e
c
o
n
v
e
n
t
i
o
n
a
l
PI
c
o
n
t
r
o
l
l
i
n
g
s
y
s
t
e
m
.
As
s
h
ow
n
in
F
i
gu
r
e
s
6
-
11
a
n
d
T
a
b
l
e
1.
W
h
e
n
us
i
n
g
PI
c
o
n
t
r
o
l
l
e
r
,
t
h
e
R
i
s
i
n
g
T
i
m
e
V
a
l
ue
=
0
.
028
98,
t
h
e
O
v
e
r
s
h
o
o
t
v
a
l
ue
=
410.
9
at
T
i
m
e
V
a
l
ue
=
0
.
0915
8
a
n
d
T
h
e
S
t
e
a
dy
-
S
t
a
t
e
E
rr
o
r
=
0
.
6297
.
W
hi
l
e
w
h
e
n
us
i
n
g
PSO
-
PI
c
o
n
t
r
o
l
l
e
r
t
h
e
R
i
s
i
n
g
T
i
m
e
v
a
l
ue
=
0.
0019
7,
t
h
e
O
v
e
r
s
h
o
o
t
v
a
l
ue
=
309.
5
at
T
i
m
e
V
a
l
ue
=
0.
009366
a
nd
S
t
e
a
dy
-
S
t
a
t
e
E
rr
o
r
=
0.
1436.
T
h
e
v
a
l
ue
s
0.
0
2701
,
0
.
486
1
a
nd
1
01.
4
a
r
e
r
e
p
r
e
s
e
n
t
e
d
t
h
e
di
f
f
e
r
e
n
c
e
of
v
a
l
ue
s
fo
r
r
i
s
i
n
g
t
i
m
e
,
s
t
e
a
dy
-
s
t
a
t
e
e
rr
o
r,
a
n
d
O
v
e
r
s
h
o
o
t
r
e
s
pe
c
t
i
v
e
l
y
w
h
e
n
us
i
n
g
PI
a
n
d
PSO
-
P
I,
t
h
e
s
e
t
hr
e
e
v
a
l
ue
s
s
h
o
w
t
h
e
r
a
ng
of
o
pt
i
m
i
z
a
t
i
o
n
in
t
h
e
pe
r
f
o
r
m
a
n
c
e
of
T
CP
/
A
Q
M
s
y
s
t
e
m
w
h
e
n
us
e
d
t
h
e
PSO
t
e
c
h
ni
que
w
i
t
h
PI
c
o
n
t
r
o
l
l
e
r
.
R
e
m
a
r
ka
b
l
y
,
t
h
e
PSO
-
PI
c
o
n
t
r
o
l
l
e
r
ha
s
i
m
p
r
o
v
e
d
t
h
e
fo
r
c
e
s
e
r
v
o
s
y
s
t
e
m
by
i
n
f
e
rr
i
n
g
t
h
e
o
pt
i
m
i
z
e
d
a
n
d
.
4.
C
O
N
C
LU
S
I
O
N
T
h
i
s
w
o
r
k
de
b
a
t
e
t
h
e
de
s
i
g
n
a
n
d
i
m
pl
e
m
e
n
t
a
t
i
o
n
of
t
h
e
s
t
a
b
i
l
i
t
y
i
s
s
ue
for
T
CP
/
A
Q
M
s
y
s
t
e
m
s
by
us
i
n
g
t
h
e
PSO
-
PI
c
o
n
t
r
o
l
l
e
r
s
.
A
c
c
o
r
di
n
g
to
s
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
s
,
t
h
e
de
s
i
g
n
e
d
PSO
-
PI
c
o
n
t
r
o
l
l
e
r
can
r
e
duc
e
t
h
e
c
o
n
ge
s
t
i
o
n
p
r
o
b
l
e
m
w
i
t
h
t
h
e
b
e
s
t
t
ra
c
ki
n
g
e
xe
c
ut
i
o
n
for
t
h
e
de
s
i
r
a
b
l
e
que
ue
bo
r
de
r
s
w
i
t
h
hi
g
h
l
i
nk
ex
pl
o
i
t
a
t
i
o
n
a
n
d
qui
c
ke
r
r
e
s
po
n
s
e
for
t
h
e
s
y
s
t
e
m
.
T
h
e
s
i
m
u
l
a
t
i
o
n
r
e
s
ul
t
s
s
h
o
w
e
d
t
ha
t
t
h
e
s
t
e
p
r
e
s
po
n
s
e
of
t
h
e
PSO
-
PI
c
o
n
t
r
o
l
l
i
n
g
s
y
s
t
e
m
is
c
o
m
pl
e
t
e
l
y
di
ff
e
r
e
n
t
f
r
o
m
t
ha
t
of
t
h
e
c
o
n
v
e
n
t
i
o
n
a
l
PI
c
o
n
t
r
o
l
l
i
n
g
s
y
s
t
e
m
,
t
h
e
i
m
p
r
o
v
e
m
e
n
t
in
T
CP
/
A
Q
M
s
y
s
t
e
m
s
w
o
r
k
be
c
o
me
c
l
e
a
r
e
s
pe
c
i
a
l
l
y
if
we
n
o
t
e
t
h
e
di
f
f
e
r
e
n
c
e
be
t
w
e
e
n
t
h
e
v
a
l
ue
s
of
r
i
s
i
n
g
t
i
m
e
,
s
t
e
a
dy
-
s
t
a
t
e
e
r
r
o
r
,
a
nd
o
ve
r
s
h
o
o
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R
EF
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[
1]
K
hudha
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r
,
A.
A
.
,
J
a
b
ba
r
,
S.
Q
.
,
S
u
l
t
t
a
n,
M.
Q
.
,
&
W
a
ng
,
D
.
,
“
W
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l
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s
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ndo
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l
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l
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z
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y
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m
s
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e
s:
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v
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y
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nd
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o
m
pa
r
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v
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ou
r
na
l
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l
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c
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l
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ne
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pu
t
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J
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E
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S)
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l
.
3
,
no
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2
,
p
p.
39
2
-
409
,
2
016
,
do
i
:
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11
591
/
i
j
e
e
c
s
.
v
3.
i
2
.
pp3
92
-
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09
.
[
2]
S
ul
t
t
a
n,
M
o
ha
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m
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d
Q
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m
,
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nt
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n
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t
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m
s
,
"
I
O
P
C
o
nf
e
r
e
nc
e
Se
r
i
e
s
:
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a
t
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r
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al
s
S
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nc
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and
E
ng
i
ne
e
r
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,
v
o
l
.
5
18,
no
.
5,
I
O
P
P
ub
l
i
s
h
i
ng
,
2019
.
[
3]
S
ul
t
t
a
n,
M
o
ha
m
m
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d
Q
a
s
i
m
,
"
I
m
pa
c
t
of
us
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I
nf
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ni
t
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m
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f
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m
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nc
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o
m
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hm
in
M
I
M
O
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y
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t
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m
s
,
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I
n
t
e
r
nat
i
on
al
J
ou
r
na
l
Of
C
om
p
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e
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s
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nd
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e
c
h
nol
ogy
,
v
o
l
.
1
5,
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.
6
,
pp
.
6857
-
6864
,
2016
,
do
i
:
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24
297
/
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j
c
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.
v
15i
6
.
16
14
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Evaluation Warning : The document was created with Spire.PDF for Python.
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do
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ne
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Sal
am
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)
135
[
4]
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o
l
o
t
,
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e
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n
-
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to
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5]
L
un,
D
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s
m
o
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S
.
,
et
al
.
,
"
O
n
c
o
di
ng
f
o
r
r
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l
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b
l
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o
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m
uni
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hy
s
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c
al
C
om
m
uni
c
a
t
i
on
,
v
o
l
.
1,
no
.
1
,
p
p.
3
-
20
,
2008
,
do
i
:
10.
1
016
/
j
.
phy
c
o
m
.
2008.
01.
006
.
[
6]
M
a
h
a
j
a
n,
M
.
,
&
K
a
ur
,
S
.
,
“
C
o
ng
e
s
t
i
o
n
C
o
nt
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l
P
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o
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W
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l
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Ne
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n
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v
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ur
v
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y
,
”
I
n
20
20
I
nt
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r
n
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onf
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C
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E
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p
p.
160
-
164
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E
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202
0
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do
i
:
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1109
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C
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48762
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202
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9160
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[
7]
W
a
ng
,
K
un,
et
al
.
,
"A
da
pt
i
v
e
f
uz
z
y
f
unne
l
c
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g
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s
t
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Q
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SA
t
r
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ns
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c
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on
s
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v
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l
.
95
,
pp.
11
-
17
,
201
9
,
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i
:
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1
016
/
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.
i
s
a
t
r
a
.
2019
.
0
5.
0
15
.
[
8]
W
a
ng
,
K
un,
et
al
.
,
"
S
t
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dy
on
T
C
P
/
A
Q
M
ne
t
w
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k
c
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s
t
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n
w
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da
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k
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r
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N
e
ur
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om
pu
t
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ng
,
v
o
l
.
363
,
pp
.
27
-
34
,
2
019
,
do
i
:
10.
10
16
/
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.
ne
uc
o
m
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08
.
024
.
[
9]
Ma
,
L
uj
ua
n
,
et
al
.
,
"
C
o
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T
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P
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Q
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nt
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na
t
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ona
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J
ou
r
na
l
of
C
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r
ol
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ut
om
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ms
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v
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l
.
18,
no
.
9,
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2
289
-
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20
20
,
do
i
:
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1007
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1255
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019
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[
10]
D
e
ng
,
W
u,
et
al
.
,
"A
nov
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l
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nt
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l
l
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a
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no
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LS
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V
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m
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hm
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g
,
v
o
l
.
23
,
no
.
7,
pp.
2
445
-
246
2
,
20
19
,
do
i
:
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.
100
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00500
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[
11]
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hne
e
n
,
S
a
l
a
m
W
a
l
e
y
,
C
he
ng
xi
o
ng
M
a
o
,
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D
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n
W
a
ng
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dv
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pt
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m
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P
S
O
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uz
z
y
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nd
PI
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l
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w
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M
S
M
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nd
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5H
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of
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r
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z
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of
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n
t
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r
na
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ona
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ou
r
na
l
of
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r
E
l
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c
t
r
on
i
c
s
and
D
r
i
v
e
Sy
s
t
e
m
s
(
I
J
P
E
D
S
)
,
v
o
l
.
7,
no
.
1,
p.
173
,
201
6
,
do
i
:
10.
11
591/
i
j
pe
d
s
.
v
7
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i
1
.
p
p173
-
19
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.
[
12]
B
a
t
o
o
l
,
M
o
ua
z
m
a
,
A
hm
a
d
J
a
l
a
l
,
a
n
d
K
i
bum
K
i
m
,
"
S
e
n
s
o
r
s
T
e
c
hn
o
l
og
i
e
s
f
o
r
H
um
a
n
A
c
t
i
v
i
t
y
A
na
l
y
s
i
s
B
a
s
e
d
on
S
V
M
O
pt
i
m
i
z
e
d
by
PSO
A
l
go
r
i
t
hm
,
"
2019
I
n
t
e
r
nat
i
o
nal
C
onf
e
r
e
nc
e
on
A
ppl
i
e
d
and
E
n
gi
ne
e
r
i
n
g
M
at
he
m
a
t
i
c
s
(
I
C
A
E
M
)
.
I
E
E
E
,
20
19
,
do
i
:
10
.
110
9/
I
C
A
E
M
.
2019
.
885
3770
.
[
13]
E
be
r
h
a
r
t
,
R
.
,
&
K
e
nne
dy
,
J.
,
“
P
a
r
t
i
c
l
e
s
w
a
r
m
o
pt
i
m
i
z
a
t
i
o
n,
”
In
P
r
oc
e
e
di
ng
s
of
t
he
I
E
E
E
i
n
t
e
r
nat
i
o
nal
c
on
f
e
r
e
nc
e
on
ne
ur
al
ne
t
w
or
k
s
,
v
o
l
.
4,
pp
.
1942
-
19
48
,
1
995
,
do
i
:
10.
11
09/
I
C
N
N
.
199
5.
4
8896
8
.
[
14]
S
hi
,
Y.
,
“
P
a
r
t
i
c
l
e
s
w
a
r
m
o
pt
i
m
i
z
a
t
i
o
n,
”
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E
E
E
c
onne
c
t
i
on
s
,
v
o
l
.
2
,
no
.
1
,
pp
.
8
-
13
,
2
004
,
do
i
:
10.
1
109
/
C
E
C
.
2001
.
9
3437
4
.
[
15]
S
hne
e
n,
S
a
l
a
m
Wa
l
e
y
,
"
A
d
v
a
nc
e
d
O
pt
i
m
a
l
f
o
r
T
hr
e
e
P
h
a
s
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R
e
c
t
i
f
i
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r
in
P
o
w
e
r
-
E
l
e
c
t
r
o
ni
c
S
y
s
t
e
m
s
,
"
I
n
done
s
i
an
J
our
nal
of
E
l
e
c
t
r
i
c
al
E
ngi
ne
e
r
i
ng
and
C
om
pu
t
e
r
Sc
i
e
nc
e
(
I
J
E
E
C
S)
,
v
o
l
.
11,
no
.
3,
pp
.
82
1
-
830
,
201
8
,
do
i
:
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1
1591
/
i
j
e
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c
s
.
v
11
.
i
3
.
p
p821
-
83
0
.
[
16]
B
a
ns
a
l
,
J.
C.
,
“
P
a
r
t
i
c
l
e
s
w
a
r
m
o
pt
i
m
i
z
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t
i
o
n,
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E
v
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l
u
t
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o
nar
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nd
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m
i
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l
l
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nc
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l
gor
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t
hm
s
,
p
p.
11
-
23
,
S
pr
i
ng
e
r
,
C
h
a
m
.
20
19
.
[
17]
C
he
ng
,
S
.
,
S
hi
,
Y
.
,
&
Q
i
n,
Q.
,
“
A
s
t
udy
of
no
r
m
a
l
i
z
e
d
po
pul
a
t
i
o
n
di
v
e
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s
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t
y
in
pa
r
t
i
c
l
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w
a
r
m
o
pt
i
m
i
z
a
t
i
o
n,
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In
H
andboo
k
of
R
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s
e
ar
c
h
on
A
d
v
an
c
e
m
e
nt
s
of
Sw
ar
m
I
n
t
e
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,
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2017
I
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E
E
C
ong
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e
s
s
on
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ol
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pp.
181
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-
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[
22]
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.
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ut
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018
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.
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24]
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25]
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u
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27]
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277
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[
28]
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be
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F
.
,
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J
.
,
&
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,
M.
F.
,
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o
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201
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30]
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32]
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[
33]
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i
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H
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,
L
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Y
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,
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34]
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35]
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v
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.
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36]
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br
y
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.
,
&
K
a
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n
,
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M.
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l
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199
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37]
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54
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38]
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ne
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3
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l
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p.
2309
-
23
14
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E
E
E
.
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:
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1
109
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2001
.
98
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39]
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o
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,
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,
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l
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47
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6
,
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.
945
-
95
9,
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002
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1
109
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.
1
0083
60
.
[
40]
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n
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A
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pu
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s
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l
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36
,
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1
,
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4
21
-
433
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:
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.
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366
-
019
-
00
767
-
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.
[
41]
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o
r
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g
o
,
M
.
,
&
S
t
ü
t
z
l
e
,
T.
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nt
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o
l
o
n
y
o
pt
i
m
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a
t
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n:
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[
42]
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[
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109
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.
27
3912
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.
[
44]
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76
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020
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11
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j
pe
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i
2
.
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62
-
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3
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[
45]
M
a
r
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i
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F
.
,
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W
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l
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k,
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,
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r
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t
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abor
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o
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s
t
e
m
s
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v
o
l
.
149
,
pp
.
153
-
165
,
2
01
5
,
do
i
:
10.
1016
/
j
.
c
h
e
m
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l
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b.
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.
08
.
0
20
.
[
46]
W
a
l
e
y
,
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a
l
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m
,
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a
c
ha
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he
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o
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phy
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s
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n
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o
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100
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[
47]
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l
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G
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o
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l
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.
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&
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t
o
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,
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ue
l
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v
o
l
.
267,
p.
117
221
,
2020
,
do
i
:
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10
16
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.
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020
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11
7221
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[
48]
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t
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l
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16
,
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1,
pp
.
65
-
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,
do
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1
1591
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49]
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.
5
56
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016
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591
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v
7.
i
1.
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3
-
192
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[
50]
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